In this project we address a new and very important issue: the observation of small backcountry wetland areas surrounded by different areas, hosting important species and delivering essential ecosystem services and biodiversity. Although these patches are small one by one, but together they can contribute to the wetland cover area with a very high rate – their protection and mapping is a need.
The MPLab laboratory is involved in the joint project SCOPIA where the task of our colleagues is to develop accurate image registration techniques for multi-spectral images: Predicting the chances of a successful Embryo transfer by the use of minimal invasive endoscopic device
Based on the APIS project, with extended goals: "To study, define, analyse a new system concept for implementing and demonstrating ISAR imaging capability in a plug-in multistatic array passive radar finalized to target recognition."
DUSIREF (Dynamic Urban Scene Interpretation and REconstruction through remotely sensed data Fusion) is a joint project of the Distributed Events Analysis Research Laboratory (DEVA) of MTA SZTAKI and Infoterra-Astrium GeoInformation Services Hungary, funded by the European Space Agency (ESA) under the PECS-HU framework. The main objective of the project is high level urban scene recognition and change interpretation based on heterogeneous Remote Sensing (RS) data sources (mainly optical and TerraSAR satellite images and LIDAR data).
The main goal of ProActive is to research a holistic citizen-friendly multi sensor fusion and intelligent reasoning framework enabling the prediction, detection, understanding and efficient response to terrorist interests, goals and curses of actions in an urban environment.To this end, ProActive will rely on the fusion of both static knowledge(i.e. intelligence information) and dynamic information (i.e. data observed from sensors deployed in the urban environment).
The integrated4D (i4D) project of MTA SZTAKI is a joint mission of the Distributed Events Analysis Research Laboratory (DEVA) and the Geometric Modelling and Computer Vision Laboratory (GMCV). The main objective of the project is to design and implement a pilot system for the reconstruction and visualisation of complex spatio-temporal scenes by integrating two different types of data: outdoor 4D point cloud sequences recorded by a car-mounted Velodyne HDL-64E LIDAR sensor, and 4D models of moving actors obtained in an indoor 4D Reconstruction Studio.
Earth observation is a growing field of interest in various application areas, such as monitoring agricultural activity, detection of pollution and environmental crimes, management of urban area expansion, crisis management, including civil protection, or homeland security. However, the evaluation of the collected remotely needs exhausting human intervention up to now due to the rich and continuously augmenting content and various aspects of assessment. For this reason, necessity of automated recognition problems in remote sensing is raised by both national and international demands.